Course notes

Below are a set of (incomplete) course notes developed for a one semester course titled Optimization theory and methods. The course has a strong numerical flavour. Typically, a mix of senior undergraduate and beginning graduate students take this course. A strong prerequisite is linear algebra, and familiarity with programming is a big bonus. The course will be offered as a MOOC from July 2024 on the NPTEL platform.

  1. Summary of background material

  2. Introduction to Optimization

  3. Unconstrained Optimization

  4. Line Search Methods

  5. Conjugate gradient methods

  6. Newton & quasi Newton methods

  7. Least squares problems

  8. Constrained optimization — first order

To be added:

  1. Projected gradient method

  2. KKT and duality

Notice:

  1. You may use these notes for academic purposes with an attribution to me and this page.

  2. You may not re-post this content anywhere without explicit permission from me.

Reference material

  1. Numerical Optimization by Nocedal and Wright, 2nd Ed. (2006) NW